Intelligent Fault Diagnosis of Bearings Based on Energy Levels in Frequency Bands Using Wavelet and Support Vector Machines (SVM)
- DOI
- 10.3390/jmmp3010011
- Published
- 2019-01-19
- Container
- Journal of Manufacturing and Materials Processing
- Publisher
- MDPI AG
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.3390/jmmp3010011,
title = {Intelligent Fault Diagnosis of Bearings Based on Energy Levels in Frequency Bands Using Wavelet and Support Vector Machines (SVM)},
author = {Seyed Majid Yadavar Nikravesh and Hossein Rezaie and Margaret Kilpatrik and Hossein Taheri},
year = {2019},
journal = {Journal of Manufacturing and Materials Processing},
doi = {10.3390/jmmp3010011},
url = {https://doi.org/10.3390/jmmp3010011}
}RIS
TY - JOUR TI - Intelligent Fault Diagnosis of Bearings Based on Energy Levels in Frequency Bands Using Wavelet and Support Vector Machines (SVM) AU - Seyed Majid Yadavar Nikravesh AU - Hossein Rezaie AU - Margaret Kilpatrik AU - Hossein Taheri PY - 2019 JO - Journal of Manufacturing and Materials Processing DO - 10.3390/jmmp3010011 UR - https://doi.org/10.3390/jmmp3010011 ER -
APA
Nikravesh, S. M. Y., Rezaie, H., Kilpatrik, M., & Taheri, H. (2019). Intelligent Fault Diagnosis of Bearings Based on Energy Levels in Frequency Bands Using Wavelet and Support Vector Machines (SVM). Journal of Manufacturing and Materials Processing. https://doi.org/10.3390/jmmp3010011
Source records
- crossref · retrieved 2026-11-10T10:45:29.883Z